Fully automated motion correction in first-pass myocardial perfusion MR image sequences.
This paper presents a novel method for registration of cardiac perfusion magnetic resonance imaging (MRI). The presented method is capable of automatically registering perfusion data, using independent component analysis (ICA) to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of that ICA. This reference image is used in a two-pass registration framework. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Despite varying image quality and motion patterns in the evaluation set, validation of the method showed a reduction of the average right ventricle (LV) motion from 1.26+/-0.87 to 0.64+/-0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65+/-7.89% to 0.87+/-3.88% between registered data and manual gold standard. Comparison of clinically relevant parameters computed using registered data and the manual gold standard show a good agreement. Additional tests with a simulated free-breathing protocol showed robustness against considerable deviations from a standard breathing protocol. We conclude that this fully automatic ICA-based method shows an accuracy, a robustness and a computation speed adequate for use in a clinical environment.
Milles
Julien
J
Division of Image Processing, Department of Radiology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
van der Geest
Rob J
RJ
Jerosch-Herold
Michael
M
Reiber
Johan H C
JH
Lelieveldt
Boudewijn P F
BP
D016477:Artifacts; D001185:Artificial Intelligence; D003287:Contrast Media; D003326:Coronary Circulation / Q000502:physiology; D006352:Heart Ventricles / Q000033:anatomy & histology; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement; D025341:Principal Component Analysis / Q000379:methods; D012016:Reference Values; D012119:Respiration; D013997:Time Factors; D015646:Ventriculography, First-Pass / Q000379:methods*
D003287:Contrast Media